DBMS > Google BigQuery vs. OpenEdge vs. Riak KV vs. Sadas Engine vs. Stardog

System Properties Comparison Google BigQuery vs. OpenEdge vs. Riak KV vs. Sadas Engine vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Application development environment with integrated database management system

Distributed, fault tolerant key-value store

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Graph DBMS
RDF store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

cloud.google.com/bigquery

www.progress.com/openedge

www.sadasengine.com

www.stardog.com

Technical documentation

cloud.google.com/bigquery/docs

documentation.progress.com/output/ua/OpenEdge_latest

www.tiot.jp/riak-docs/riak/kv/latest

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.stardog.com

Developer

Google

Progress Software Corporation

OpenSource, formerly Basho Technologies

SADAS s.r.l.

Stardog-Union

Initial release

2010

1984

2009

2006

2010

Current release

OpenEdge 12.2, March 2020

3.2.0, December 2022

8.0

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

free trial version available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

C++

Java

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X

AIX
Linux
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Import/export of XML data possible

Secondary indexes

yes

restricted

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

close to SQL 92

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Progress proprietary ABL (Advanced Business Language)

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
C
C#
C++
Groovy
Java
PHP
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Erlang

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

pre-commit hooks and post-commit hooks

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

since Version 11.4

Sharding

no "single point of failure"

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users and groups

yes, using Riak Security

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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